Slidify

library(shiny)
runGitHub('ekstroem/ShinyLeastSquares')

The "role" of graphics is changing and expanding

Necesary packages etc XXX To be filled out at the end

Rstudio

See also: Toby's link

devtools::install_github("ramnathv/rCharts")

Tobys slides terms / discussion

• multi-layer, multi-panel, multi-plot
• animation, direct manipulation (clicking, hovering), indirect manipulation (buttons, menus)
• zoom, highlight, show/hide (data, labels, tooltips)

http://cbio.ensmp.fr/~thocking/WorldBank-facets/

HighCharter

happiness$size <- sqrt(happiness$population)/8
hap <- happiness # Shorten name
happy2 <- highchart() %>%
  hc_title(text = "Taxes and happiness") %>%
  hc_subtitle(text = "Source: Wikipedia") %>%
  hc_xAxis(title = list(text = "Taxation (%)")) %>%
  hc_yAxis(title = list(text = "Happiness")) %>%
  hc_chart(zoomType = "xy") %>%
  hc_exporting(enabled = TRUE) %>%
  hc_add_serie_scatter(hap$tax, hap$happy,
                       hap$size, hap$continent, hap$country,
                       dataLabels = list( enabled = TRUE,
                                    format = "{point.label}")
                       ) %>%
  hc_tooltip(useHTML = TRUE,
             headerFormat = "<table>",
             pointFormat = paste("<tr><th colspan=\"1\"><b>{point.label}</b></th></tr>",
                                 "<tr><th>Tax</th><td>{point.x} %</td></tr>",
                                 "<tr><th>Score</th><td>{point.y}</td></tr>",
                                 "<tr><th>Pop</th><td>{point.z} </td></tr>",
                                 "<tr><th>Cont.</th><td>{point.valuecolor} hp</td></tr>",
                                 "<tr><th>Religion</th><td>{point.extrainfo} hp</td></tr>"),

             footerFormat = "</table>")
happy2

Take the airquality dataset. Plot series of temperature and wind speed for June.

data(airquality)
aq <- subset(airquality, Month==6)
head(aq)

library(highcharter)
hc <- highchart() %>%
  hc_chart(type = "column") %>%
  hc_title(text = "Denmark") %>%
  hc_xAxis(categories = aq$Day) %>% 
  hc_yAxis_multiples(
    list(title = list(text = "Temperature (F)")), 
    list(opposite=TRUE, title = list(text = "Speed (MPH)"))) %>%
 ...

dygraphs

Should be the same as before (happyness)

metricsgraphics

Time series, line charts, scatterplots, histograms, bar charts and data tables, rug plots and basic linear regression.

Same idea as highcharter/dygraphs.

library(RColorBrewer)

tmp <- data.frame(year=seq(1790, 1970, 10), uspop=as.numeric(uspop))

tmp %>%
  mjs_plot(x=year, y=uspop) %>%
  mjs_point() %>%
  mjs_add_marker(1850, "Something Wonderful") %>%
  mjs_add_baseline(150, "Something Awful")

") | | Legend | hc_legend(enabled=FALSE) | | Credits | hc_credits(enabled = TRUE, text = "Source: Wikipedia", href = "https://wikipedia.com", style = list(fontSize = "12px")) |

leaflet

Beautiful maps crated by adding layers on top of maps.

library(leaflet)

m <- leaflet() %>%
  addTiles() %>%  # Default OpenStreetMap map tiles
  addMarkers(lat=37.431106, lng=-122.164672, popup="useR 2016") 
m 

Main functions

| Function | Example | |——–+———-| | Default map | addTiles() | | Alternative maps | addProviderTiles("CartoDB.DarkMatter", options = providerTileOptions(opacity = 0.35)) Stackable! | | Markers | addMarkers(~long, ~lat, popup = ~as.character(mag)) | | Pop-ups | addPopups(lng=-122.164672, lat=37.431106, "<a href='http://www.user2016.org'> Hi </a>", options = popupOptions(closeButton = FALSE)) | | Custom icons | makeIcon() |

library(leaflet)
library(MESS)

pal <- colorNumeric("RdYlBu", 
                    domain = NULL)
data(earthquakes)
m <- leaflet(subset(earthquakes,  mag>3)) %>%
  addProviderTiles("CartoDB.DarkMatter") %>%  
addCircleMarkers(
    radius = ~ mag*3,
    color  = ~ pal(depth),
    stroke = FALSE, fillOpacity = 0.4
  )
m

Create your own icon and pop-up on this map.

Add the R icon to the map: https://www.r-project.org/logo/Rlogo.png

(Use icon instead of popup in addMarkers)

Create simple icon:

greenLeafIcon <- makeIcon(
  iconUrl = "http://leafletjs.com/docs/images/leaf-green.png",
  iconWidth = 38, iconHeight = 95,
  iconAnchorX = 22, iconAnchorY = 94
)

Note: html/js output. Need javascript machinery to run (ie., html with js code embedded or online link).

library(htmlwidgets)
saveWidget(widget, file, selfcontained = TRUE, background="white")

Including in R markdown

htmlwidget widgets behave nicely in R markdown.

Otherwise

as.iframe to appear.

Use ggplot2 (and grammar of graphics) to render interactive graphics.

• ggplotly use the plot.ly service
• ggiraph uses it's own htmlwidget extensions.

plotly

Use legend to toggle traces, zoom, shift and click to pan. Super simple: p <- ggplot() ; ggplotly(p)

p <- ggplot(happiness, 
            aes(x=tax, y=happy, color=continent, size=population, 
                text = paste("country:", country))) + 
  geom_point( alpha = I(0.8)) + 
  scale_size_area(max_size = 30) + 
  geom_smooth(method="lm", se= F, size = 1, 
              aes(linetype = continent, group = continent))
ggplotly(p)

On plotly

xxxx

Extends ggplot2 with new geom functions.

• geom_point_interactive
• geom_polygon_interactive
• geom_map_interactive
• geom_path_interactive
• geom_rect_interactive
• geom_segment_interactive
• geom_text_interactive

Three arguments let you add interactivity:

• tooltip: mouse-over tooltips to be displayed when mouse is over elements.
• onclick: javascript function to be executed when elements are clicked.
• data_id: id to be associated with elements.

library(ggiraph)

happiness$tooltip <- paste0("<table><th>Welcome to</th><tr><td>", 
                            happiness$country, 
                            "</td></tr></table>")

p <- ggplot(happiness, 
            aes(x=tax, y=happy, color=continent, 
                size=population, tooltip=tooltip)) + 
  geom_point_interactive(alpha=I(.8)) + 
  scale_size_area(max_size = 30)

ggiraph(code = {print(p)}, height = "350px")

library(ggiraph)

happiness$tooltip <- paste0("<table><th>Welcome to</th><tr><td>", happiness$country, "</td></tr></table>")


happiness$onclick <- sprintf(
  "window.open(\"%s%s\")",
  "http://en.wikipedia.org/wiki/",
  as.character(happiness$country)
)

happiness$data_id <- happiness$country

p <- ggplot(happiness, 
            aes(x=tax, y=happy, color=continent, 
                size=population, tooltip=tooltip, onclick=onclick)) + 
  geom_point_interactive(alpha=I(.8)) + 
  scale_size_area(max_size = 30)

ggiraph(code = print(p), 
        hover_css = "fill-opacity:.3;cursor:pointer;",
           height = "350px")

ggiraph

Use standard R. Rather simple and beautiful. Simple input - no fancy transitions. Requires server

library(shiny)
runGitHub('ekstroem/ShinySampleMean')

Library

ui.R

server.R

Running apps from Github